CUDA performance tuning requires understanding how code maps to GPU hardware architecture. The guide covers the execution model (threads, warps, blocks, grids), hardware constraints (streaming multiprocessors, registers, memory hierarchy), and memory optimization (coalescing, shared memory bank conflicts). It explains how to
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Table of contents
IntroductionKey TakeawaysWhat is CUDA?CUDA Execution Model: Threads, Warps, Blocks, and GridsGPU Architecture Basics (Affecting Performance)CUDA Memory HierarchyPerformance Models That Engineers UseOptimization Playbook: Symptom → Cause → FixConcurrency: Streams and OverlapConclusionFAQsReferencesSort: